Abstract
As the most significant nonlinear reservoir, the rocks have complex structural characteristic. The pore structure of the rock is varied in shape and complex in connectivity. However, the prevailing methods for characterising the microstructure of rocks, such as the coordination number method and fractal theory, are still difficult to quantify the structural properties. In this study, based on the CT-scan method and a new complex network theory, the topological characteristics of rocks such as seepage path selection, degree of pore aggregation, pore importance, and pore module structure are analysed. The results show that the scale-free network model is more reliable in characterising the rock pore network than previously published structural models, and a small number of pores are the “key” to the seepage process. Besides, we proposed a new method to quantify the importance of rock pores and present the distribution characteristics and connectivity laws of the rock-pore network. This provides a new method to study the seepage process of the nonlinear reservoirs.
Highlights
The highly complex network of pore throats is the main conduit for CBM migration during the extraction [1–4]
The digital core of shale with different porosity was extracted by Kelly et al using FIB-scanning electron microscopy (SEM), and the coordination-number method is used to explore the network connectivity of shale pores [14]
Based on complex network theory, this paper presents a comprehensive analysis of the distribution patterns of rock networks such as average path length, degree distribution, the importance of pores in the seepage process, and the characteristics of pore aggregation
Summary
The highly complex network of pore throats is the main conduit for CBM migration during the extraction [1–4]. The digital core of shale with different porosity was extracted by Kelly et al using FIB-SEM, and the coordination-number method is used to explore the network connectivity of shale pores [14]. Based on digital cores of shale, Yang et al proposed a superposition algorithm capable of analysing both organic and inorganic pores of the matrix [15]. The rock pore structure is highly complex, and the conventional network models still have major difficulties in characterising pore connectivity and other topologies [21–23]. Based on complex network theory, this paper presents a comprehensive analysis of the distribution patterns of rock networks such as average path length, degree distribution, the importance of pores in the seepage process, and the characteristics of pore aggregation. The results of this study provide a rational approach to reveal the micromechanics of porous rocks
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